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So here I am in the Amazon Kinesis service.

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And I wanna show you just the options

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for Kinesis data analytics.

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So here it is.

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So we have two different kinds of things.

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You can either create a streaming application

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or go into the studio.

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The streaming application is actually just

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all leveraging app Apache Flink.

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This is the case analytics for Apache Flink.

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You choose a runtime version

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for Apache Flink that's supported

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and then you can have the application name.

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And then, at some point,

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you need to enter your production information.

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And this would create a streaming application

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that you can use on AWS.

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And so you would need to actually upload then

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your application here.

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As we see when we get there

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and we don't have any Apache Flink application available

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to us, because this is quite complex, right?

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Then you can run and you can even monitor it

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using the Apache Flink dashboard.

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So this service is to create Apache Flink applications.

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And actually, if you wanted to just do one of analysis

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you can open a studio notebook

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and this will just quickly create a notebook

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where you can start running your streaming applications

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again, leveraging Apache Flink.

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Okay. So this I will not do.

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And then where is the Apache,

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where is the Amazon Kinesis data analytics

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for SQL applications?

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Well, it's on the left hand side

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and this is where it would be.

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So you would find it under the SQL applications legacy

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and now they recommend that you use all the time

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Kinesis data analytics studio and Apache Flink?

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But if you wanted to, for example, read from

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Kinesis Data Firehose, you would create a SQL applications

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in the legacy form and you would enter actually

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the application name and it did create one.

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And then once you've define your application name,

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you can actually go to realtime analytics

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and write the kind of SQL you want to do

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for this application, okay?

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So it's just an overview.

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You don't need to know anything

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about Kinesis data analytics for this exam

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but I wanna show you the options,

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give you a quick introduction.

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And so you could visualize it as well on the console.

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So that's it for this lecture.

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I hope you liked it.

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And I will see you in the next lecture.